Lead AI Engineer

At Veracity, we aim to be a different kind of insurance partner – one that is free from outside investors, venture capital, or the pressures of a corporate parent. Ours is a culture of empowerment – one that believes in effort, results, and accountability. We believe that transparency fosters trust, trust fosters growth, and that growth drives innovation. Our commitment to rigorous evaluation and relentless execution lead to rapid evolution. We answer only to the small business owners we serve, and this independence allows us to stay focused on what matters most: helping their businesses thrive by providing expert guidance and best-in-class insurance policies. We’re growing fast and want you to be a part of it! We are seeking a Lead AI Engineer to serve as our organization's foremost technical authority on artificial intelligence strategy, architecture, and adoption. At Veracity, that means shaping how AI is built and scaled across a customer-facing digital insurance platform serving small business owners nationwide – from how we surface coverage recommendations to how we prepare for a world where AI agents increasingly research and purchase insurance on behalf of human customers. This is not a people management role – it is a systems leadership role. You will act as the connective tissue between engineering, product, and business leadership, making and owning the high-stakes technical decisions: build vs. buy, platform selection, architectural patterns, and AI tooling standards. You will bring structure and discipline to our AI practice while operating with the urgency and adaptability of a fast-moving, independent company. Key Responsibilities Technical Strategy & Direction Define the AI engineering roadmap and architecture standards across the organization Lead build vs. buy vs. integrate decision-making for AI systems and platforms – and be accountable for articulating how you arrived at those decisions Evaluate emerging tools, frameworks, and models; provide clear, defensible recommendations to leadership Serve as the ultimate technical escalation point for complex AI/ML system design challenges Enterprise Systems & Scaling Architect AI solutions for our enterprise platform – which has already been substantially rebuilt and requires thoughtful evolution, not ground-up construction Design systems for scale, reliability, and cost-efficiency in production environments Establish LLMOps practices – evaluation and regression suites for LLM-powered features, cost and quality observability, versioned prompts/configs with staged rollout and rollback, and production guardrails Ensure AI systems integrate cleanly with existing product and engineering infrastructure Cross-Functional Collaboration Partner closely with Product and Engineering leadership to align AI capabilities with business outcomes Receive operational support to help initiate and coordinate cross-functional engagement, allowing you to stay focused on technical leadership and decision-making Provide clear guidance on resource allocation – who owns what, who should be engaged, and in what sequence Translate complex technical concepts for non-technical audiences, including executives and business stakeholders Challenge direction constructively and push back on approaches that compromise long-term system health AI Coding & Process Transformation Champion and introduce AI-assisted coding practices and developer tooling across the engineering organization Define standards for responsible AI development including guardrails, evaluation frameworks, and security considerations Drive continuous improvement in how the organization builds and ships AI-powered features What This Role Is Not This is not a people manager role. You will not carry direct reports or be evaluated on team headcount. You may provide technical direction to contributors, but managing people is the exception, not the expectation. Requirements and Qualifications Required Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field (or equivalent practical experience) 8+ years of software engineering experience, with demonstrated mastery designing and shipping production systems where correctness, reliability, and auditability matter 2+ years building production LLM/GenAI and agentic systems, plus fluency with AI-assisted coding tooling and the judgment to set org-wide standards, evals, and guardrails for AI-generated code Sound judgment about where AI belongs and where it must not – comfortable with probabilistic agents for customer-facing and research tasks, while keeping policy binding, money movement, and compliance flows deterministic, auditable, and human-governed Experience making and communicating build vs. buy vs. integrate decisions at an organizational level Proficiency in Python and the modern GenAI application stack – agent/orchestration frameworks (e.g. LangChain, LlamaIndex, or equivalents), model-provider SDKs, vector databases, and evalua